Technical Writing

A systematic framework for LLM agents to tackle hard optimization and debugging problems. Covers theoretical floors, structured worklogs, agent architecture, bottleneck hierarchy, the wall protocol, optimization patterns, and SQLite-based memory systems.

A framework for LLM agents to systematically explore and understand complex systems, codebases, and problem spaces. Covers uncertainty mapping, exploration journals, agent roles (Surveyor, Diver, Tracer, Synthesizer, Challenger), and memory systems.

Rigorous evidence-based market validation for SJSON serialization format. Testable hypotheses, triangulated demand signals, transparent scoring rubric, and behavioral proof from ML platforms, Graph ML, Protobuf, and Arrow ecosystems.

An autonomous scientific discovery engine that extracts, validates, and synthesizes claims from ML research papers. Builds a knowledge graph with regime-gated edges and mines it for testable hypotheses using anti-hype scoring.

A soccer prediction system combining Elo ratings, Bayesian calibration, and Monte Carlo simulation. Features walk-forward backtesting, multi-league support, season odds simulation, and evidence-based betting strategy analysis.

A hybrid memory system for LLM agents combining SQLite for structured storage, embeddings for semantic search, and Zettelkasten-style linking. Used by both debugging and exploration protocols.